All Projects → goktug97 → NEATEST

goktug97 / NEATEST

Licence: MIT License
NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to NEATEST

DeepHyperNEAT
A public python implementation of the DeepHyperNEAT system for evolving neural networks. Developed by Felix Sosa and Kenneth Stanley. See paper here: https://eplex.cs.ucf.edu/papers/sosa_ugrad_report18.pdf
Stars: ✭ 42 (+223.08%)
Mutual labels:  neat, genetic-algorithm, neuroevolution
NeuroEvolution-Flappy-Bird
A comparison between humans, neuroevolution and multilayer perceptrons playing Flapy Bird implemented in Python
Stars: ✭ 17 (+30.77%)
Mutual labels:  neat, genetic-algorithm, neuroevolution
Evolutionsimulator
Evolution Simulator with Box2D
Stars: ✭ 143 (+1000%)
Mutual labels:  genetic-algorithm, neuroevolution, evolutionary-algorithms
neuro-evolution
A project on improving Neural Networks performance by using Genetic Algorithms.
Stars: ✭ 25 (+92.31%)
Mutual labels:  neat, genetic-algorithm, neuroevolution
GARI
GARI (Genetic Algorithm for Reproducing Images) reproduces a single image using Genetic Algorithm (GA) by evolving pixel values.
Stars: ✭ 41 (+215.38%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
geneticalgorithm2
Supported highly optimized and flexible genetic algorithm package for python
Stars: ✭ 36 (+176.92%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
Neatron
Yet another NEAT implementation
Stars: ✭ 14 (+7.69%)
Mutual labels:  genetic-algorithm, neuroevolution
opt4j
Modular Java framework for meta-heuristic optimization
Stars: ✭ 25 (+92.31%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
neuroevolution-robots
Neuroevolution demo through TensorFlow.js, Neataptic, and Box2D
Stars: ✭ 31 (+138.46%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
zoofs
zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
Stars: ✭ 142 (+992.31%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
GeneticAlgorithmForFeatureSelection
Search the best feature subset for you classification mode
Stars: ✭ 82 (+530.77%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
biteopt
Derivative-Free Optimization Method for Global Optimization (C++)
Stars: ✭ 91 (+600%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
evo-NEAT
A java implementation of NEAT(NeuroEvolution of Augmenting Topologies ) from scratch for the generation of evolving artificial neural networks. Only for educational purposes.
Stars: ✭ 34 (+161.54%)
Mutual labels:  neat, neuroevolution
neat-openai-gym
NEAT for Reinforcement Learning on the OpenAI Gym
Stars: ✭ 19 (+46.15%)
Mutual labels:  neat, neuroevolution
exact
EXONA: The Evolutionary eXploration of Neural Networks Framework -- EXACT, EXALT and EXAMM
Stars: ✭ 43 (+230.77%)
Mutual labels:  neuroevolution, evolutionary-algorithms
goga
Go evolutionary algorithm is a computer library for developing evolutionary and genetic algorithms to solve optimisation problems with (or not) many constraints and many objectives. Also, a goal is to handle mixed-type representations (reals and integers).
Stars: ✭ 39 (+200%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
evoli
Genetic Algorithm and Particle Swarm Optimization
Stars: ✭ 22 (+69.23%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
tiny gp
Tiny Genetic Programming in Python
Stars: ✭ 58 (+346.15%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
EvOLuTIoN
A simple simulation in Unity, which uses genetic algorithm to optimize forces applied to cubes
Stars: ✭ 44 (+238.46%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms
triangula
Generate high-quality triangulated and polygonal art from images.
Stars: ✭ 3,775 (+28938.46%)
Mutual labels:  genetic-algorithm, evolutionary-algorithms

NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training

It is NEAT but the weights are trained with Natural Evolution Strategy and the weights are shared across genomes.

Requirements

numpy
cloudpickle

Install

pip install nesneat

Optional

matplotlib # To draw networks
mpi4py # For parallelization
gym # For examples

Usage

Check examples

PYTHONPATH="$(pwd):$PYTHONPATH" python examples/cartpole.py
# Or in parallel
PYTHONPATH="$(pwd):$PYTHONPATH" mpirun -np 2 python examples/cartpole.py
Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].